Optimizing chemotherapy treatment outcomes using metaheuristic optimization algorithms: A case study

Samy, Prakas Gopal and Kanesan, Jeevan and Badruddin, Irfan Anjum and Kamangar, Sarfaraz and Ahammad, N. Ameer (2024) Optimizing chemotherapy treatment outcomes using metaheuristic optimization algorithms: A case study. Bio-Medical Materials and Engineering, 35 (2). pp. 191-204. ISSN 0959-2989, DOI https://doi.org/10.3233/BME-230149.

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Official URL: https://doi.org/10.3233/BME-230149

Abstract

BACKGROUND: This study explores the dynamics of a mathematical model, utilizing ordinary differential equations (ODE), to depict the interplay between cancer cells and effector cells under chemotherapy. The stability of the equilibrium points in the model is analysed using the Jacobian matrix and eigenvalues. Additionally, bifurcation analysis is conducted to determine the optimal values for the control parameters. OBJECTIVE: To evaluate the performance of the model and control strategies, benchmarking simulations are performed using the PlatEMO platform. METHODS: The Pure Multi-objective Optimal Control Problem (PMOCP) and the Hybrid Multi-objective Optimal Control Problem (HMOCP) are two different forms of optimal control problems that are solved using revolutionary metaheuristic optimisation algorithms. The utilization of the Hypervolume (HV) performance indicator allows for the comparison of various metaheuristic optimization algorithms in their efficacy for solving the PMOCP and HMOCP. RESULTS: Results indicate that the MOPSO algorithm excels in solving the HMOCP, with M-MOPSO outperforming for PMOCP in HV analysis. CONCLUSION: Despite not directly addressing immediate clinical concerns, these findings indicates that the stability shifts at critical thresholds may impact treatment efficacy.

Item Type: Article
Funders: University of Malaya International Collaboration Grant, University of Malaya, Malaysia (ST023-2022), Centre for Advanced Electrical and Electronic Systems (CAEES), Faculty of Engineering, Built Environment & Information Technology, SEGi University, King Khalid University King Saud University (RGP.1/330/44)
Uncontrolled Keywords: Multi-objective optimal control problem; metaheuristic optimization algorithms; bifurcation analysis; stability analysis
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Department of Electrical Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 14 Nov 2024 03:20
Last Modified: 14 Nov 2024 03:20
URI: http://eprints.um.edu.my/id/eprint/45889

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